A new co-authored research paper on "Rain-on-snow (ROS) based flooding" got published recently. We showed how ROS events contribute to actual flooding and identified the causal structure leading to ROS floods in different regions of the globe.
Paper link: doi.org/10.1016/j.jh...
This study used machine learning to identify key drivers of evapotranspiration, highlighting the importance of hydrometeorological and biomass variables for better predictions.
@kanakkantikar.bsky.social
onlinelibrary.wiley.com/doi/full/10....
#MachineLearning
Hydrology Paper of the Day @kanakkantikar.bsky.social on partitioning ET using machine learning to determine the importance of drivers: hydroecological variables and datasets; application to the Reynolds Creek Critical Zone Observatory; random forests and explainable AI; and a novel framework.
Happy to share our garden-fresh paper on "ET partitioning using flux tower data in a semi-arid ecosystem" (t.ly/7z9s8). It introduces that combining hydromet and biomass productivity variables improved the predictions of ET and its components.
#hydrologicalprocesses
